Software Engineering Commons^™

Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group, Yating Lin, Kamkwai Wong, Yong Wang, Rong Zhang, Bo Dong, Huamin Qu, Qinghua Zheng

Research Collection School Of Information Systems

Tax evasion is a serious economic problem for many countries, as it can undermine the government’s tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related ...

Tradao: A Visual Analytics System For Trading Algorithm Optimization, Ka Wing Tsang, Haotian Li, Fuk Ming Lam, Yifan Mu, Yong Wang, Huamin Qu

Research Collection School Of Information Systems

With the wide applications of algorithmic trading, it has become critical for traders to build a winning trading algorithm to beat the market. However, due to the lack of efficient tools, traders mainly rely on their memory to manually compare the algorithm instances of a trading algorithm and further select the best trading algorithm instance for the real trading deployment. We work closely with industry practitioners to discover and consolidate user requirements and develop an interactive visual analytics system for trading algorithm optimization. Structured expert interviews are conducted to evaluateTradAOand a representative case study is documented for illustrating the system ...

Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma

Research Collection School Of Information Systems

With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students’ problem-solving processes unfold step by step to infer whether students’ problem-solving logic matches their design intent. They also need to compare the behaviors of different groups (e.g., students from different grades) to distribute questions to students with the right level of knowledge. The availability of fine-grained interaction data, such as mouse movement trajectories ...

Visual Analysis Of Discrimination In Machine Learning, Qianwen Wang, Zhenghua Xu, Zhutian Chen, Yong Wang, Yong Wang, Huamin Qu

Research Collection School Of Information Systems

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set ...

Distributed Load Testing By Modeling And Simulating User Behavior, Chester Ira Parrott

LSU Doctoral Dissertations

Modern human-machine systems such as microservices rely upon agile engineering practices which require changes to be tested and released more frequently than classically engineered systems. A critical step in the testing of such systems is the generation of realistic workloads or load testing. Generated workload emulates the expected behaviors of users and machines within a system under test in order to find potentially unknown failure states. Typical testing tools rely on static testing artifacts to generate realistic workload conditions. Such artifacts can be cumbersome and costly to maintain; however, even model-based alternatives can prevent adaptation to changes in a system ...

Methodological Aspects Of Distance Learning For Developing The Professional Competence Of Students Of The Direction "Computer Engineering, B Kузнетсова, Gulnora Мухтарова, Umida Azimova, Ким Елена

Bulletin of TUIT: Management and Communication Technologies

This work is based on the use of distance learning technologies in education, which will make it possible to individualize training, and in turn contributes to the formation of professionally important qualities for students of the direction of "Computer Engineering". The experimental work was aimed at developing a technology for the formation of students' professional competence.

The article shows that the mastery by students of knowledge, skills and abilities in the field of computer engineering was aimed at their conscious application in solving problems of the educational and cognitive process, and subsequently in professional activity.

The article presents the results ...

Implementation Of An Electronic Alert For Improving Adherence To Diabetic Foot Exam Screenings In Type 2 Diabetic Patients In Primary Care Clinics, Ruby Denson

Student Scholarly Projects

Practice Problem: Patients with type 2 diabetes mellitus (T2DM) are at an increased risk of complications including foot ulcerations (Harris-Hayes et al., 2020). Preventive care is essential for the early detection of foot ulcers but despite the advantages of preventive screening, a limited number of primary care providers perform annual foot exams (Williams et al., 2018).

PICOT: The clinical question that guided this project was, “In adult patients with T2DM receiving care in a primary care setting, will the implementation of an electronic clinical reminder alert (ECR) increase provider adherence to performing an annual diabetic foot exam and risk assessment ...

Extended Functionalities For Automating Comic Book Pull Files, Jackson Cunningham

Theses/Capstones/Creative Projects

This Honors Thesis project involves programming additional features for a Java application developed as a team for the UNO Computer Science Capstone Project. The purpose of this Capstone project was to develop an updated Pull File system for Dragon’s Lair Comics & Games, which has been running an outdated system in need of improvement. The pull file is an organizational system used by customers to reserve new issues of specific on-going comic book series as they are released. The comic book store can use a pull file system to maintain records of customers, store inventory, and order requests, gaining important ...

Smartfuzz: An Automated Smart Fuzzing Approach For Testing Smartthings Apps, Lwin Khin Shar, Nguyen Binh Duong Ta, Lingxiao Jiang, David Lo, Wei Minn, Kiah Yong Glenn Yeo, Eugene Kim

Research Collection School Of Information Systems

As IoT ecosystem has been fast-growing recently, there have been various security concerns of this new computing paradigm. Malicious IoT apps gaining access to IoT devices and capabilities to execute sensitive operations (sinks), e.g., controlling door locks and switches, may cause serious security and safety issues. Unlike traditional mobile/web apps, IoT apps highly interact with a wide variety of physical IoT devices and respond to environmental events, in addition to user inputs. It is therefore important to conduct comprehensive testing of IoT apps to identify possible anomalous behaviours. On the other hand, it is also important to optimize ...

Mcst : An App For Patron Awareness Of Covid-19 Safety Measures Instituted By Small Businesses, Jorge Torres

Theses, Dissertations and Culminating Projects

Small businesses across America are having restrictions placed upon them due to the COVID-19 pandemic. Those fortunate enough to remain open now face the challenge of trying to generate enough revenue to stay afloat. Small businesses, with their lack of funds, have resorted to listing their safety precautions on their front door to inform patrons. However, viewing these rules would require patrons to leave their homes. Additionally, there is no consistent set of rules being enforced by the government which is dangerous as some patrons may feel that stricter procedures be in place. These inconsistencies and lack of information can ...

Actor Concurrency Bugs: A Comprehensive Study On Symptoms, Root Causes, Api Usages, And Differences, Mehdi Bagherzadeh, Nicholas Fireman, Anas Shawesh, Raffi T. Khatchadourian

Publications and Research

Actor concurrency is becoming increasingly important in the development of real-world software systems. Although actor concurrency may be less susceptible to some multithreaded concurrency bugs, such as low-level data races and deadlocks, it comes with its own bugs that may be different. However, the fundamental characteristics of actor concurrency bugs, including their symptoms, root causes, API usages, examples, and differences when they come from different sources are still largely unknown. Actor software development can significantly benefit from a comprehensive qualitative and quantitative understanding of these characteristics, which is the focus of this work, to foster better API documentations, development practices ...

Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker

Research Collection School Of Information Systems

Android as an operating system is now increasingly being adopted in industrial information systems, especially with Cyber-Physical Systems (CPS). This also puts Android devices onto the front line of handling security-related data and conducting sensitive behaviors, which could be misused by the increasing number of polymorphic and metamorphic malicous applications targeting the platform. The existence of such malware threats therefore call for more accurate identification and surveillance of sensitive Android app behaviors, which is essential to the security of CPS and IoT devices powered by Android. Nevertheless, achieving dynamic app behavior monitoring and identification on real CPS powered by Android ...

Jito: A Tool For Just-In-Time Defect Identification And Localization, Fangcheng Qiu, Meng Yan, Xin Xia, Xinyu Wang, Yuanrui Fan, Ahmed E. Hassan, David Lo

Research Collection School Of Information Systems

In software development and maintenance, defect localization is necessary for software quality assurance. Current defect localization techniques mainly rely on defect symptoms (e.g., bug reports or program spectrum) when the defect has been exposed. One challenge task is: can we locate buggy program prior to the appearance of the defect symptom. Such kind of localization is conducted at an early stage (e.g., when buggy program elements are being checkedin) which can be an early step of continuous quality control.In this paper, we propose a Just-In-Time defect identification and lOcalization tool, named JITO, which can help developers to ...

"Authors On The Hill " Presents Prof. Giovanni Spani, Giovanni Spani

Authors on the Hill

Professor Giovanni Spani of the World Languages, Literatures, and Cultures Department at the College of the Holy Cross will present his work on Dante's Florence, a multimedia educational app for Android and iOS.

A Survey On Deep Geometry Learning: From A Representation Perspective, Yun-Peng Xiao, Yu-Kun Lai, Fang-Lue Zhang, Chunpeng Li, Lin Gao

Computational Visual Media

Researchers have achieved great success in dealing with 2D images using deep learning. In recent years, 3D computer vision and geometry deep learning have gained ever more attention. Many advanced techniques for 3D shapes have been proposed for different applications. Unlike 2D images, which can be uniformly represented by a regular grid of pixels, 3D shapes have various representations, such as depth images, multi-view images, voxels, point clouds, meshes, implicit surfaces, etc. The performance achieved in different applications largely depends on the representa-tion used, and there is no unique representation that works well for all applications. Therefore, in this survey ...

S4net: Single Stage Salient-Instance Segmentation, Ruochen Fan, Ming-Ming Cheng, Qibin Hou, Tai-Jiang Mu, Jingdong Wang, Shi-Min Hu

Computational Visual Media

In this paper, we consider salient instance segmentation. As well as producing bounding boxes, our network also outputs high-quality instance-level segments as initial selections to indicate the regions of interest. Taking into account the category-independent property of each target, we design a single stage salient instance segmentation framework, with a novel segmentation branch. Our new branch regards not only local context inside each detection window but also the surrounding context, enabling us to distinguish instances in the same scope even with partial occlusion. Our network is end-to-end trainable and is fast (running at 40 fps for images with resolution 320 ...

Saliency-Based Image Correction For Colorblind Patients, Jinjiang Li, Xiaomei Feng, Hui Fan

Computational Visual Media

Improper functioning, or lack, of human cone cells leads to vision defects, making it impossible for affected persons to distinguish certain colors. Colorblind persons have color perception, but their ability to capture color information differs from that of normal people: colorblind and normal people perceive the same image differently. It is necessary to devise solutions to help persons with color blindness understand images and distinguish different colors. Most research on this subject is aimed at adjusting insensitive colors, enabling colorblind persons to better capture color information, but ignores the attention paid by colorblind persons to the salient areas of images ...

3d Hypothesis Clustering For Cross-View Matching In Multi-Person Motion Capture, Miaopeng Li, Zimeng Zhou, Xinguo Liu

Computational Visual Media

We present a multiview method for markerless motion capture of multiple people. The main challenge in this problem is to determine cross-view correspondences for the 2D joints in the presence of noise. We propose a 3D hypothesis clusteringtechnique to solve this problem. The core idea is to transform joint matching in 2D space into a clustering problem in a 3D hypothesis space. In this way, evidence from photometric appearance, multiview geometry, and bone length can be integrated to solve the clustering problem efficiently and robustly. Each cluster encodes a set of matched 2D joints for the same person across different ...

Psychological Potential Field And Human Eye Fixation On Binary Line-Drawing Images: A Comparative Experimental Study, Naoyuki Awano, Yuki Hayashi

Computational Visual Media

Quantitatively evaluating the psychological and perceptual effects of objects is an important issue, but is difficult. In cognitive studies, the psychologicalpotential field (PPF), which represents psychological intensities in vision and can be calculated by applying computational algorithms to digital images, may help with this issue. Although studies have reported using the PPF to evaluate psychological effects, such as impressions, detailed investigations on how the PPF represents psychological perception and its limitations have not yet been performed. Another relevant tool is the fixation map, which visualizes human eye fixations; this map is generated from actual measurements acquiredby eye-tracking and does not ...

Jmnet: A Joint Matting Network For Automatic Human Matting, Xian Wu, Xiao-Nan Fang, Tao Chen, Fang-Lue Zhang

Computational Visual Media

We propose a novel end-to-end deep learning framework, the Joint Matting Network (JMNet), to automatically generate alpha mattes for human images. We utilize the intrinsic structures of the human body as seen in images by introducing a pose estimation module, which can provide both global structural guidance and a local attention focus for the matting task. Our network model includes a pose network, a trimap network, a matting network, and a shared encoder to extract features for the above three networks. We also append a trimap refinement module and utilize gradient loss to provide a sharper alpha matte. Extensive experiments ...